Horia-Nicolai Teodorescu

Intelligent systems and technologies in rehabilitation engineering

INTRODUCTION New Technologies in Rehabilitation: General Trends SENSORIAL PROSTHESES A Retinal Prosthesis to Benefit the Visually Impaired Intelligent Techniques in Hearing Rehabilitation LOCOMOTOR PROSTHESES Sensory Feedback for Lower Limb Prostheses Multifunction Control of Prostheses using the Myoelectric Signal Selective Activation of the Nervous System for Motor System Neural Prostheses Upper Limb Myoelectric Prostheses: Sensory Control System and Automatic Tuning of Parameters PACEMAKERS AND LIFE-SUSTAINING DEVICES Computer-Aided Support Technology for Artificial Heart Control: Diagnosis and Hemodynamic Measurements Diaphragm Pacing for Chronic Respiratory Insufficiency Intelligent Systems in Heart Pacemakers ROBOTIC SYSTEMS AND ADVANCED MECHANICS Service Robots for Rehabilitation and Assistance Computerized Obstacle Avoidance Systems for the Blind and Visually Impaired Advanced Design Concepts for a Knee-Ankle-Foot Orthosis Index of Acronyms and Abbreviations Index of Terms

Fuzzy methods in tremor assessment, prediction, and rehabilitation

Tremor is a disabling condition for a large segment of population, mainly elderly. To the present date, there are no adequate tools to diagnose and help rehabilitation of subjects with tremor, but recently there is a tremendous surge of interest in the research in the field. We report on the use of fuzzy methods in applications for rehabilitation, namely in tremor diagnosing and control. We synthesize our results regarding the characterization of the tremor by means of nonlinear dynamics techniques and fuzzy logic, and the prediction of tremor movements in view of rehabilitation purposes. Based on linear and nonlinear analysis of tremor, and using fuzzy aggregation, the fusing of tremor parameters in global functional disabling factors is proposed. Nonlinear dynamic parameters, namely correlation dimension and Lyapunov exponent is used in order to improve the assessment of tremor. The benefits of the fuzzy fused tremor parameters rely on more complete and accurate assessment of the functional impairment and on improved feedback for rehabilitation, based on the fused parameters of the tremor. Further steps in rehabilitation may require external muscular control. In turn, the control of tremor by electrical stimulation requires movement prediction. Several neural and neuro-fuzzy predictors are compared and a neuro-fuzzy predictor is presented, allowing us five-step ahead prediction, with an RMS error of the order of 10%. The benefits of the neuro-fuzzy predictor are good prediction capability, versatility, and apparently a high robustness to individual variations of the tremor. The reported research, which extended over several years and included development of sensors, equipment, and software, has been aimed to development of products. The results may also open new ways in tremor rehabilitation.

Intelligent systems and interfaces

Preface. Acknowledgments. About the Editors. Contributors. Part 1: Intelligent Agents and Bio-Inspired Systems. 1. A tutoring based approach to the development of intelligent agents G. Tecuci, et al. 2. An object-oriented framework for building collaborative network agents L. Boloni, D.C. Marinescu. 3. Animals versus robotic autonomous agents J.E.R. Staddon, I.M. Chelaru. 4. From configurable circuits to bio-inspired systems M. Sipper, et al. Part 2: Intelligent Data Processing. 5. Fuzzy data mining A. Kandel, A. Klein. 6. Feature-oriented hybrid neural adaptive systems and applications H.-N. Teodorescu, C. Bonciu. 7. Algebraic neuro-fuzzy systems and applications H.-N. Teodorescu, D. Arotaritei. Part 3: Interfaces. 8. Neuro-fuzzy approach to natural language understanding and processing. Part I: Neuro-fuzzy device E. Ferri, G. Langholz. 9. Neuro-fuzzy approach to natural language understanding and processing. Part II: Neuro-fuzzy learning algorithms E. Ferri, G. Langholz. 10. Graph matching and similarity H. Bunke, Xiaoyi Jiang. Part 4: Applications and High-tech Management. 11. Diagnosis systems and strategies: principles, fuzzy and neural approaches P.M. Frank, T. Marcu. 12. Intelligent non-destructive testing and evaluation with industrial applications C. Morabito. 13. Managing high-tech projects. Part I D. Mlynek, P. Mali. 14. Managing high-tech projects. Part II D. Mlynek, P. Mali. Index of Terms.

A fuzzy information space approach to speech signal non-linear analysis

A new approach for analyzing the similarity of dynamical systems is presented, with applications to speech analysis. This approach is based on a temporal fuzzy set representation of the trajectories of the dynamical system. The similarity between segments of the speech signal is determined via similarity measures of the corresponding temporal fuzzy sets. We present an application of the method to vowel recognition in the samples (amplitude–time) space. © 2000 John Wiley & Sons, Inc.

Analysis of chaotic movements and fuzzy assessment of hands tremor in rehabilitation

The analysis of chaotic components in movements during hands tremor and more classic analysis of the movements is considered in relation to its application to diagnosis and rehabilitation techniques. Fuzzy methods are used to characterize the movements and to assess their normality. Visual and auditory feedback is provided to help controlling the movements in a rehabilitation system that incorporates elements of virtual reality.

Report of research activities in fuzzy AI and medicine at USF CSE

Several projects involving the use of fuzzy and neuro-fuzzy methods in medical applications, developed by members of the Department of Computer Science and Engineering, University of South Florida, Tampa, Florida, are briefly reviewed. The successful applications are emphasized.

Nonlinear analysis and selection of relevant parameters in assessing the treatment results of reducing tremor, using DBS procedure

The DBS (deep brain stimulation) is an invasive method of applying electrical stimulus to a sum of thalamic nucleus and represents a successful method for reducing the tremor. The aim of this research is to find a method to determine if there are abnormal responses to DBS for patients with Parkinson. DBS being an invasive method, it is indicated to determine if the method gives good results in a specific case before we pursuit with this neuro-surgical procedure. We computed the Lyapunov exponent, the fractal dimension and the self-correlation function to assess the relevance of nonlinear dynamic parameters in tremor analysis. To model a nonlinear process like Parkinsonian tremor we considered an iterated nonlinear function, which is easy to implement.

Nonlinear Dynamics Sensitivity Analysis in Networks and Applications to Sensing 1

Abstract We present an extended framework and software tools for the analysis of the non-linear dynamical (chaotic) processes in networks of identical systems and in hybrid networks. The systems are characterized by several external and internal parameters, and the evolution of the dynamics in the multidimensional space of the parameters is investigated. Extensions of the bifurcation diagram are introduced as theoretical tools, and related software tools to analyze the patterns in the parametric space are presented. Based on this analysis, the development of a new class of sensors, relaying on chaotic processes, with capabilities of data fusing and pattern recognition is presented. Several applications are discussed. Experimental results with circuits implementing several applications are also presented and discussed